b'Amy Zhang'

Model-Invariant State Abstractions for Model-Based Reinforcement Learning

Accuracy and generalization of dynamics models is key to the success of ...
02/19/2021 ∙ by Manan Tomar, et al. ∙ 2 ∙ share

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Multi-Task Reinforcement Learning with Context-based Representations

The benefit of multi-task learning over single-task learning relies on t...
02/11/2021 ∙ by Shagun Sodhani, et al. ∙ 18 ∙ share

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Pano: Engaging with News using Moral Framing towards Bridging Ideological Divides

Society is showing signs of strong ideological polarization. When pushed...
01/27/2021 ∙ by Jessica Wang, et al. ∙ 0 ∙ share

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Automating Document Classification with Distant Supervision to Increase the Efficiency of Systematic Reviews

Objective: Systematic reviews of scholarly documents often provide compl...
12/09/2020 ∙ by Xiaoxiao Li, et al. ∙ 13 ∙ share

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Intervention Design for Effective Sim2Real Transfer

The goal of this work is to address the recent success of domain randomi...
12/03/2020 ∙ by Melissa Mozifian, et al. ∙ 2 ∙ share

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Multi-Task Reinforcement Learning as a Hidden-Parameter Block MDP

Multi-task reinforcement learning is a rich paradigm where information f...
07/14/2020 ∙ by Amy Zhang, et al. ∙ 16 ∙ share

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Learning Invariant Representations for Reinforcement Learning without Reconstruction

We study how representation learning can accelerate reinforcement learni...
06/18/2020 ∙ by Amy Zhang, et al. ∙ 9 ∙ share

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Plan2Vec: Unsupervised Representation Learning by Latent Plans

In this paper we introduce plan2vec, an unsupervised representation lear...
05/07/2020 ∙ by Ge Yang, et al. ∙ 8 ∙ share

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Invariant Causal Prediction for Block MDPs

Generalization across environments is critical to the successful applica...
03/12/2020 ∙ by Amy Zhang, et al. ∙ 2 ∙ share

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Stable Policy Optimization via Off-Policy Divergence Regularization

Trust Region Policy Optimization (TRPO) and Proximal Policy Optimization...
03/09/2020 ∙ by Ahmed Touati, et al. ∙ 6 ∙ share

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Out-of-Distribution Generalization via Risk Extrapolation (REx)

Generalizing outside of the training distribution is an open challenge f...
03/02/2020 ∙ by David Krueger, et al. ∙ 25 ∙ share

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Improving Sample Efficiency in Model-Free Reinforcement Learning from Images

Training an agent to solve control tasks directly from high-dimensional ...
10/02/2019 ∙ by Denis Yarats, et al. ∙ 18 ∙ share

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Learning Causal State Representations of Partially Observable Environments

Intelligent agents can cope with sensory-rich environments by learning t...
06/25/2019 ∙ by Amy Zhang, et al. ∙ 68 ∙ share

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Natural Environment Benchmarks for Reinforcement Learning

While current benchmark reinforcement learning (RL) tasks have been usef...
11/14/2018 ∙ by Amy Zhang, et al. ∙ 6 ∙ share

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A Dissection of Overfitting and Generalization in Continuous Reinforcement Learning

The risks and perils of overfitting in machine learning are well known. ...
06/20/2018 ∙ by Amy Zhang, et al. ∙ 0 ∙ share

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Decoupling Dynamics and Reward for Transfer Learning

Current reinforcement learning (RL) methods can successfully learn singl...
04/27/2018 ∙ by Amy Zhang, et al. ∙ 0 ∙ share

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Composable Planning with Attributes

The tasks that an agent will need to solve often are not known during tr...
03/01/2018 ∙ by Amy Zhang, et al. ∙ 0 ∙ share

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Mapping the world population one building at a time

High resolution datasets of population density which accurately map spar...
12/15/2017 ∙ by Tobias G. Tiecke, et al. ∙ 0 ∙ share

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Building Detection from Satellite Images on a Global Scale

In the last several years, remote sensing technology has opened up the p...
07/27/2017 ∙ by Amy Zhang, et al. ∙ 0 ∙ share

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Feedback Neural Network for Weakly Supervised Geo-Semantic Segmentation

Learning from weakly-supervised data is one of the main challenges in ma...
12/08/2016 ∙ by Xianming Liu, et al. ∙ 0 ∙ share

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Guess Who Rated This Movie: Identifying Users Through Subspace Clustering

It is often the case that, within an online recommender system, multiple...
08/09/2014 ∙ by Amy Zhang, et al. ∙ 0 ∙ share

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Amy Zhang

Featured Co-authors

Sergey Levine

Pieter Abbeel

Aaron Courville

Anima Anandkumar

Joelle Pineau

Doina Precup

Yarin Gal

Zachary C Lipton

Andrea Montanari

Thomas S. Huang

Arthur Szlam

Model-Invariant State Abstractions for Model-Based Reinforcement Learning

Multi-Task Reinforcement Learning with Context-based Representations

Pano: Engaging with News using Moral Framing towards Bridging Ideological Divides

Automating Document Classification with Distant Supervision to Increase the Efficiency of Systematic Reviews

Intervention Design for Effective Sim2Real Transfer

Multi-Task Reinforcement Learning as a Hidden-Parameter Block MDP

Learning Invariant Representations for Reinforcement Learning without Reconstruction

Plan2Vec: Unsupervised Representation Learning by Latent Plans

Invariant Causal Prediction for Block MDPs

Stable Policy Optimization via Off-Policy Divergence Regularization

Out-of-Distribution Generalization via Risk Extrapolation (REx)

Improving Sample Efficiency in Model-Free Reinforcement Learning from Images

Learning Causal State Representations of Partially Observable Environments

Natural Environment Benchmarks for Reinforcement Learning

A Dissection of Overfitting and Generalization in Continuous Reinforcement Learning

Decoupling Dynamics and Reward for Transfer Learning

Composable Planning with Attributes

Mapping the world population one building at a time

Building Detection from Satellite Images on a Global Scale

Feedback Neural Network for Weakly Supervised Geo-Semantic Segmentation

Guess Who Rated This Movie: Identifying Users Through Subspace Clustering